It is our great pleasure to welcome you to the Workshop on Software Engineering Methods for Parallel and High Performance Applications -- SEM4HPC 2017.
The workshop aims to discuss parallel computing beyond traditional scientific computing and using them to develop enterprise and industrial applications. Compared to the traditional sequential computing paradigm, the software development, analysis and migration tools for parallel and high performance applications are far less matured for the IT industry to make a shift towards the new computing paradigm. The mission of this workshop is to bring the global industry and academic experts in this area to identify various research challenges that exist in software engineering methods for parallel and high performance application development, maintenance and migration. The workshop also aims to bring out the current state of the art and practice of the software engineering methods through case-studies, novel research ideas, and keynote and invited talks.
The call for papers attracted submissions from the Netherlands, India, and the United States. We received five technical papers out of which three were selected with an acceptance ratio of 60%.
We also encourage attendees to attend the keynote and invited talk presentations. These valuable and insightful talks can and will guide us to a better understanding of challenges in this area:
Keynote: "MPI Acceleration of Image Classification: Are We Seeing the Resurgence of MPI in Solving Big Data Problems?", Sameer Kumar (IBM Research, India)
Invited Talk: "READEX Tool Suite for Energy-efficiency Tuning of HPC Applications", Michael Gerndt (Technical University of Munich, Germany)
Proceeding Downloads
MPI Acceleration of Image Classification: Are We Seeing the Resurgence of MPI in Solving Big Data Problems?
Recent work has shown the effectiveness of the MPI programming paradigm in accelerating image classification via the Stochastic Gradient Descent optimization technique. Applications such as Caffe, Torch and Tensor Flow, that use Graphic Processing Unit ...
How Effective is Design Abstraction in Thrust?: An Empirical Evaluation
High performance computing applications are far more difficult to write, therefore, practitioners expect a well-tuned software to last long and provide optimized performance even when the hardware is upgraded. It may also be necessary to write software ...
READEX Tool Suite for Energy-efficiency Tuning of HPC Applications
The European Union Horizon 2020 READEX project is developing a tool suite for dynamic energy tuning of HPC applications. The tool suite performs an analysis during design-time before production run to construct a tuning model encapsulated with the best-...
PRESGen: A Fully Automatic Equivalence Checker for Validating Optimizing and Parallelizing Transformations
Petri net has been a popular choice of model of computation (MoC) for representing parallel programs. PRES+ is an extension of the traditional Petri net model which is specially equipped to precisely model embedded systems. Since multi-core and ...
Using High Level GPU Tasks to Explore Memory and Communications Options on Heterogeneous Platforms
Heterogeneous computing platforms that use GPUs for acceleration are becoming prevalent. Developing parallel applications for GPU platforms and optimizing GPU related applications for good performance is important. In this work, we develop a set of ...
Index Terms
- Proceedings of the 2017 Workshop on Software Engineering Methods for Parallel and High Performance Applications
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
SEM4HPC '17 | 5 | 3 | 60% |
SEM4HPC '16 | 11 | 5 | 45% |
Overall | 16 | 8 | 50% |